代码搜索：classifier
找到约 4,824 项符合「classifier」的源代码
代码结果 4,824
www.eeworm.com/read/150749/12267161
m latentlssvm.m
function [zt,model] = latentlssvm(varargin)
% Calculate the latent variables of the LS-SVM classifier at the given test data
%
% >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)
www.eeworm.com/read/150749/12267300
m latentlssvm.m
function [zt,model] = latentlssvm(varargin)
% Calculate the latent variables of the LS-SVM classifier at the given test data
%
% >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)
www.eeworm.com/read/149739/12352675
m minc.m
%MINC Minimum combining classifier
%
% W = MINC(V)
% W = V*MINC
%
% INPUT
% V Set of classifiers
%
% OUTPUT
% W Minimum combining classifier on V
%
% DESCRIPTION
% If V = [V1,V2,V3, ...
www.eeworm.com/read/149739/12353500
m votec.m
%VOTEC Voting combining classifier
%
% W = VOTEC(V)
% W = V*VOTEC
%
% INPUT
% V Set of classifiers
%
% OUTPUT
% W Voting combiner
%
% DESCRIPTION
% If V = [V1,V2,V3,...] is a stacked set of
www.eeworm.com/read/149739/12354003
m maxc.m
%MAXC Maximum combining classifier
%
% W = MAXC(V)
% W = V*MAXC
%
% INPUT
% V Stacked set of classifiers
%
% OUTPUT
% W Combined classifier using max-rule
%
% DESCRIPTION
% If V = [V1,V2,V
www.eeworm.com/read/119681/14824438
m latentlssvm.m
function [zt,model] = latentlssvm(varargin)
% Calculate the latent variables of the LS-SVM classifier at the given test data
%
% >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)
www.eeworm.com/read/214923/15082914
m latentlssvm.m
function [zt,model] = latentlssvm(varargin)
% Calculate the latent variables of the LS-SVM classifier at the given test data
%
% >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)
www.eeworm.com/read/213240/15139995
m plotroc.m
function h = plotroc(e,varargin)
%PLOTROC Draw an ROC curve
%
% H = PLOTROC(W,A)
% H = PLOTROC(E)
%
% Plot the roc curve of E according to the 'traditional' way: on the x
% axis we put the fal
www.eeworm.com/read/293183/8310571
m binm.m
%BINM Binary mapping for classifier outcomes
%
% W = W*binm
%
% Binary transformation of a map or a classifier.
%
% binm transforms the outcomes of the classifier or map
% to binary using the maxim
www.eeworm.com/read/172172/9722052
m latentlssvm.m
function [zt,model] = latentlssvm(varargin)
% Calculate the latent variables of the LS-SVM classifier at the given test data
%
% >> Zt = latentlssvm({X,Y,'classifier',gam,sig2,kernel}, {alpha,b}, Xt)